Metadata-Version: 1.0
Name: SparkSafeDelta
Version: 0.3.0
Summary: Combination of tools that allow more convenient use of PySpark within Azure DataBricks environment.
Home-page: http://pypi.python.org/pypi/SparkSafeDelta/
Author: Aleksandrs Krivickis
Author-email: aleksandrs.krivickis@gmail.com
License: LICENSE.txt
Description: ==================================
        # Spark Safe Delta
        ==================================
        
        Combination of tools that allow more convenient use of PySpark within Azure DataBricks environment.
        
        ## Package contents:
        =========
        
        ### 1.delta_write_safe
        -------------
        Tool that allows to automatically update schema of DataBricks Delta in case of Changes in data structure
        
        ### 1.write_data_mysql
        -------------
        Method writes data into MySQL and takes care of repartitioning in case if it's necessary.
        
            Dependencies:
              1. MySQL connector Java 8_0_13
              dbfs:/FileStore/jars/7b863f06_67cf_4a51_8f3b_67d414d808b3-Barnymysql_connector_java_8_0_13_4ac45-2f7c7.jar
        
              http://dev.mysql.com/doc/connector-j/en/
              https://mvnrepository.com/artifact/mysql/mysql-connector-java
        
            By default, it relies on constant variables outside of method that define MySQL credentials, that can be also specified as a parameters:
                * MYSQL_URL
                * MYSQL_DRIVER
                * MYSQL_USER
                * MYSQL_PASSWORD
                * MYSQL_SSL_CA_PATH
                * MYSQL_QUERY_TIMEOUT
        
            Method Parameters:
               * p_spark_dataframe - dataframe to write
               * p_mysql_db_name - name of database to write to
               * p_mysql_table_name - name of table to write to
               * p_num_partitions - amount of partitions, if -1, runs with default amount of partitions defined in spark environment or specific delta
        
            Method default parameters:
                p_num_partitions=-1
                url=MYSQL_URL,
                driver=MYSQL_DRIVER,
                user=MYSQL_USER,
                password=MYSQL_PASSWORD,
                ssl_ca=MYSQL_SSL_CA_PATH,
                queryTimeout=MYSQL_QUERY_TIMEOUT
        
            Usage example:
              #MySQL settings defined outside of a method below:
              MYSQL_DRIVER = "com.mysql.jdbc.Driver"
              MYSQL_URL = "jdbc:mysql://hostname:port/database?useUnicode=true&characterEncoding=utf-8&useJDBCCompliantTimezoneShift=true&useLegacyDatetimeCode=false"
              MYSQL_QUERY_TIMEOUT = 0
        
              MYSQL_USER = "user@namespace"
              MYSQL_PASSWORD = "example_password"
              MYSQL_SSL_CA_PATH = "/mnt/alex-experiments-blob/certs/cert.txt"
        
              #Method execution itself
              write_data_mysql(p_spark_dataframe=target_data, p_mysql_dbtable=destination_db_name_column_name_construct)
        
        ### 3.remove_columns
        -------------
            remove_columns() method removes columns from a specified dataframe.
            It will silently return a result even if user specifies column that doesn't exist.
            Usage example: destination_df = remove_columns(source_df, "SequenceNumber;Body;Non-existng-column")
        
        ### 4.read_mysql
        -------------
            Method allows fetch the table, or a query as a Spark DataFrame.
            Returnws Spark DataFrame as a result.
        
            # Example usage:
            read_mysql(table_name=customers)
            read_mysql(table_name=h2.customers)
            read_mysql(table_name=h2.customers, url=MYSQL_URL, driver=MYSQL_DRIVER, user=MYSQL_USER, password=MYSQL_PASSWORD, ssl_ca=MYSQL_SSL_CA_PATH, queryTimeout=MYSQL_QUERY_TIMEOUT)
        
        ### 4.list_available_mysql_tables
        -------------
            Method allows to list all the tables that available to a particular user.
            Returnws Spark DataFrame as a result
        
        
        ## Package sample usage:
        =========
            ``
            #!/usr/bin/env python
            
            from sparksafedelta import sparksafedelta
            sparksafedelta.delta_write_safe(sp_df_to_write, SP_CONTEXT, DATABRICKS_TABLE_NAME)
            ``
Platform: UNKNOWN
